• KSCE Journal of Civil and Environmental Engineering Research
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• v.26 no.1B
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• pp.39-50
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• 2006

The flood control offices of main rivers have used a storage function model to forecast flood stage in Korea and studies of flood forecasting actively have been done even now. On this account, the storage function model, which is used in flood control office, regression models and artificial neural network model are applied into flood forecasting of study watershed in this paper. The result obtained by each method are analyzed for the comparative study. In case of storage function model, this paper uses the representative parameters of the flood control offices and the optimized parameters. Regression coefficients are obtained by regression analysis and neural network is trained by backpropagation algorithm after selecting four events between 1995 to 2001. As a result of this study, it is shown that the optimized parameters are superior to the representative parameters for flood forecasting. The results obtained by multiple, robust, stepwise regression analysis, one of the regression methods, show very good forecasts. Although the artificial neural network model shows less exact results than the regression model, it can be efficient way to produce a good forecasts.

• Journal of Wetlands Research
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• v.17 no.3
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• pp.237-244
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• 2015

This study is estimated the flood damage probability of the flood discharge, the flood stage estimation and Economic Analysis for Flood Control about considering of uncertainty. Sum River Basin has chosen and the probability precipitation is estimated by using the concept of critical rainfall duration depending on the frequency of each flood stage estimation point. For calculating the expected annual damage, the functions of long term hazard, discharge-frequency, stage-discharge and depth-damage are established for 8 areas in Sum River Basin. The expected annual damaged is obtained which is based on the sampling informations through more than 500,000 simulation from the functions of considered uncertainty. The result about the optimum frequency and Investment Priorities are estimated by conducting the evaluation about planning the levee of various of Design Frequency. In analysis result, 12% of B/C value has increased if the uncertainty has concerned. Also the optimum frequency or Investment Priorities are possible to be changed. If the political and social analysis perform together it would be helpful to have a reasonable decision other than only the economical analysis as actual Flood damaged reduction planning.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.36 no.6
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• pp.1011-1021
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• 2016

This study performs the potential flood hazard analysis by applying elevation data, soil data and land use data. The susceptibility maps linked to elevation, soil and land use are combined to develop the new types of flood hazard map such as runoff production map and runoff accumulation map. For the development of the runoff production map, land use, soil thickness, permeability, soil erosion and slope data are used as runoff indices. For the runoff accumulation map, elevation, knick point and lowland analysis data are used. To derive an integrated type of flood potential hazard, a TOPSIS (The Technique for Order of Preference by Similarity to Ideal Solution) technique, which is widely applied in MCDM (Multi-Criteria Decision Making) process, is adopted. The indices applied to the runoff production and accumulation maps are considered as criteria, and the cells of analysis area are considered as alternatives for TOPSIS technique. The model is applied to Gamcheon watershed to evaluate the flood potential hazards. Validation with large scale data shows the good agreements between historical data and runoff accumulation data. The analysis procedure presented in this study will contribute to make preliminary flood hazard map for the public information and for finding flood mitigation measures in the watershed.

• Journal of Korea Water Resources Association
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• v.40 no.3
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• pp.223-236
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• 2007

Recently in urban area flood damages increase due to local concentrated heavy rainfall. Even in the cities where stormwater drainage systems are relatively well established flood damage still occurs because of the capacity limitations of the existing stormwater drainage systems. When the flood exceeds the capacity limitation of the urban storm sewer system, it yields huge property losses of public facilities involving roadway inundation to paralyze industrial and transportation system of the city. To prevent such flood damages in urban area, it is necessary to develop adequate inundation analysis model which can consider complicated geometry of urban area and artificial drainage system simultaneously. The Dual-Drainage model used in this study is the urban inundation analysis model which combines SWMM with DEM based 2-dimensional surface flood inundation model. In this study, the dual drainage model has been modified to consider the effect of complex buildings in urban area. Through the simulation of time variable inundation process, it is possible to identify inundation alert locations as well as to establish emergency action plan for the residencial area vulnerable to flood inundation.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.38 no.5
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• pp.671-683
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• 2018

The flood damage caused by heavy rains in urban watershed is increasing, and, as evidenced by many previous studies, urban flooding usually exceeds the water capacity of drainage networks. The flood on the area which considerably urbanized and densely populated cause serious social and economic damage. To solve this problem, deterministic and probabilistic studies have been conducted for the prediction flooding in urban areas. However, it is insufficient to obtain lead times and to derive the prediction results for the flood volume in a short period of time. In this study, IDNN, TDNN and NARX were compared for real-time flood prediction based on urban runoff analysis to present the optimal real-time urban flood prediction technique. As a result of the flood prediction with rainfall event of 2010 and 2011 in Gangnam area, the Nash efficiency coefficient of the input delay artificial neural network, the time delay neural network and nonlinear autoregressive network with exogenous inputs are 0.86, 0.92, 0.99 and 0.53, 0.41, 0.98 respectively. Comparing with the result of the error analysis on the predicted result, it is revealed that the use of nonlinear autoregressive network with exogenous inputs must be appropriate for the establishment of urban flood response system in the future.

• Journal of the Korean Society of Hazard Mitigation
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• v.10 no.2
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• pp.143-149
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• 2010

The river master plan was established every 10 years in Korea. The basin characteristics of 62 small and medium size rivers of which master plans were recently established during the past three years in Gyeonggi-do were investigated, and design rainfalls and design floods in the past and the latest were compared and analyzed. It was predicted that basin data and flood estimating method changed design flood. The quantitative amount of design floods were analyzed for 6 basins like Gungunchen etc. As the results, the increasing factors of design flood were the application of critical duration time, temporal time of rainfall and the increase of CN value. The decreasing factors of design flood were the application of Huff's rainfall distribution instead of Mononobe one and the ARF. The application of critical duration time increased flood about 60% whereas the application of Huff's rainfall distribution method estimated less flood than Mononobe about 62%. Considering critical duration time and changing rainfall distribution were the most important factors of increasing or decreasing design flood. However, trends of flood variation were differently analyzed by factors in 6 basins because characteristics of topography, weather, hydrology and hydraulic were different, now that correlations were not found between factors and flood variation. Flood variation is evaluated by complex effects of factors so new flood recalculated by reasonable methods should be considered as design flood.

• 한국방재학회:학술대회논문집
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• 2007.02a
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• pp.571-574
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• 2007

The purpose of this research is to analyze sensitivities on hydraulic characteristic factors of bridge and culvert causing flood water level rising. With HEC-RAS and RMA2 models, analysis of backwater due to bridge and culvert in an ideal stream was carried out. The results of hydraulic modeling and sensitivity analysis indicated that the opening ratio and the Froude number were the most sensitive factors and other factors were not quite sensitive to flood water level rising.

• Journal of Korean Society for Geospatial Information Science
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• v.25 no.2
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• pp.49-56
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• 2017

In this study, flood analysis was conducted to prepare for damage caused by typhoons and heavy rain due to abnormal climate and climate change. Two - dimensional flooding analysis using the FLUMEN model, which is widely used for national and international flood risk mapping, was conducted for the Nam River Basin, which is the tributary of the Nakdong River. This study divides the topography into $5m{\times}5m$ DEM by ArcView, so that the accuracy of river repair and hydrological characterization and flood area identification can be maximized. As a result of simulation of water flooding, 163.3ha in section 1, 227.7ha in section 2 and 59.9ha in section 3 were simulated.

• Journal of the Society of Disaster Information
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• v.11 no.1
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• pp.55-62
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• 2015

This study suggested Nationwide Inundation Analysis method for Storm and Flood Damage Insurance Rate. Suggested modified Level-Pool method considers Zoning of urban plan to reflect real inundated area and limit inundation-boundary. Inundated area, as results of modified Level-Pool method, compared with inundation risk area on "storm and flood damage mitigation total plan". Simulated inundated area by modified Level-Pool method was more matched than results of traditional method. Therefore, modified Level-Pool method could be useful to analyze nationwide inundated area.

• Journal of The Korean Society of Agricultural Engineers
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• v.48 no.5
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• pp.17-27
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• 2006

The objective of this study is to induce the design floods by the methodology of L-moment including test of homogeneity, independence and outlier of the data of annual maximum flood flows for 12 water level gaging stations of South Korea. To select appropriate distribution of the data for annual maximum flood flows, the distributions of Wakeby and Kappa are applied and the appropriateness is judged by Kolmogorov-smirnov (K-S) test. The parameters of selected Wakeby and Kappa distributions are calculated by the method of L-moment and the design floods are induced. Through the comparative analysis using the relative root mean square errors (RRMSE) and relative absolute errors (RAE) of design floods, the result shows that the design floods by Wakeby distribution are closer to the observed data than those obtained by the Kappa distribution.